PROJECT SUMMARY Millions of people world-wide are affected by diseases and conditions related to the immune system. Unfortunately, the current supply of approved anti-inflammatory medicine is very limited and only treats a small fraction of inflammatory diseases; many of these treatments also cause severe side-effects with long-term use. Nearly half of the drugs on the market today are natural products and natural product derivatives. The long-term objective of my research is to continue efforts toward the discovery of diverse chemical compounds and their mechanism of action (MOA) to inspire the next generation of novel therapeutics. This proposal approaches this objective by utilizing known bioactive chemical libraries, new advanced technologies to allow for improved high-content phenotypic screens, and computational tools for data processing and analysis. In collaboration with natural product chemists, we have access to unique libraries of natural botanical and marine product extracts. The Lokey lab has shown that a high-content image-based screening platform called, cytological profiling (CP) in HeLa cells is a valuable tool to give insights about the potential MOA of lead compounds at the primary screening stage based on a limited staining set that probes the cell cycle, organelles, and the cytoskeleton. Therefore, we have developed an image-based screening platform that preliminary data suggests improves the resolution of biological annotation by including pro-inflammatory stimuli, lipopolysaccharide (LPS) and immunologically relevant primary bone marrow derived macrophages. The central issue that my proposal addresses is the lack of a well established high-throughput screening methods for the direct prediction of compound MOA. Further improvements that need to be addressed are resolving sub-category clustering, identifying anti-inflammatories, and building a database toward assigning biological functions to natural product mixture components. In the course of our proposed studies we will: 1) Expand the resolving power and increase the phenotypic ?sensitivity? by including transiently activated signaling proteins downstream of the Toll Like Receptor-4 (TLR4) pathway. 2) Build a reference database to categorize unknown compound fingerprints and predict the mechanism of action of natural products extracts. We will develop a robust cytological profiling pipeline for the classification of natural products based on their phenotypic similarity to known bioactive compounds. My graduate training will expand my knowledge of chemical biology, innate immune responses to pathogens, and provide me with bioinformatics and programming tools to establish myself as an independent researcher. Furthermore, these contributions are significant because they will resolve fundamental technological barriers for the prediction of MOA in complex natural product mixtures and provide new tools to continue the discovery of biologically relevant diverse compounds with unique chemical space.